Project Summary Human immunodeficiency virus (HIV) infected (HIV+) people have up to 50% excess risk of atherosclerotic cardiovascular disease (ASCVD, i.e. acute myocardial infarction, ischemic stroke) compared to uninfected people. This excess ASCVD risk is not explained by traditional cardiovascular disease (CVD) risk factors (e.g. smoking, hypertension). Liver disease is common among HIV+ people, and the liver regulates immuno- metabolic processes associated with atherosclerosis (e.g. inflammation, dyslipidemia and microbial translocation). Whether liver injury is in the causal pathway between HIV and incident ASCVD is unknown. The objective of this application is to understand whether liver injury contributes to the excess risk of ASCVD among HIV+ compared to uninfected people. The knowledge gained will be used to assess ways to improve existing ASCVD risk prediction tools in HIV+ populations. For these objectives, we will leverage existing NHLBI/NIAAA-funded cohorts to: 1) assess whether liver injury mediates the relationship between HIV infection and excess ASCVD risk; 2) investigate associations between liver injury and biomarkers of a) subclinical CVD, b) immuno-metabolism by HIV status; and 3) assess whether accounting for liver injury improves ASCVD risk prediction in HIV. If liver injury explains some of the excess ASCVD risk observed among HIV+ people, this would have important implications: It would reveal a novel, preventable, potentially reversible ASCVD risk factor (liver injury) that results in worse clinical outcomes for HIV+ compared to uninfected people. Two innovations in this study are: 1) the use of existing data from the Veteran's Aging Cohort Study (VACS), a large (N~150,000), national sample of HIV+ and uninfected Veterans with a rich collection of longitudinal clinical data; and 2) a causal inference strategy combining epidemiological studies of clinical ASCVD events, mechanistic studies of subclinical atherosclerosis risk and ASCVD risk prediction. Dr. So-Armah has a PhD in Epidemiology, experience designing and conducting biostatistical analyses, and a strong publication and collaboration record in the field of HIV, comorbid diseases and CVD. To successfully complete this career development award, he will pursue further didactic, experiential (clinical rotations), and professional training. With the activities proposed in this application, he will transition to an independent investigator, with expertise in novel potential mechanisms of CVD (e.g. liver injury), in the setting of HIV. He will be able to combine 1) population and clinical science, 2) understanding of pathology at the molecular level, 3) causal inference epidemiology and biostatistics methods, and 4) big data analytics to answer questions of public health importance in HIV and CVD. This inter-disciplinary K01 application is supported by a multi- disciplinary mentorship team that has a history of successful collaboration and expertise spanning HIV, hepatology, CVD, causal inference, longitudinal data analysis, and population, clinical and basic sciences.